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Kalman filter lithium battery SOC estimation method based on model parameter optimization

A technology of Kalman filtering and model parameters, which is applied in the direction of measuring electricity, measuring electrical variables, measuring devices, etc., can solve the problems of large estimation error and low online estimation accuracy

Inactive Publication Date: 2019-10-22
HENAN POLYTECHNIC UNIV
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Problems solved by technology

However, the current Kalman filter method estimates SOC online, the estimation error is relatively large, and the online estimation accuracy is low.

Method used

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  • Kalman filter lithium battery SOC estimation method based on model parameter optimization
  • Kalman filter lithium battery SOC estimation method based on model parameter optimization
  • Kalman filter lithium battery SOC estimation method based on model parameter optimization

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Embodiment Construction

[0130] The present invention will be further described below with specific embodiment, and the schematic embodiment of the present invention and explanation are used for explaining the present invention, but are not as the limitation of the present invention.

[0131] Such as Figure 1 to Figure 11 Shown a kind of Kalman filter lithium battery SOC estimation method based on model parameter optimization, comprises the following steps:

[0132] S1, establish the second-order RC equivalent circuit model of lithium battery;

[0133] S2. Initialize the open circuit voltage VOC and SOC of the lithium battery, and identify the parameters of the second-order RC equivalent circuit model on the basis of obtaining the OCV-SOC relationship curve;

[0134] S3. After identifying the parameters of the second-order RC equivalent circuit model, verify the accuracy of the model;

[0135] S4. Establishing a Kalman filter algorithm based on the second-order RC equivalent circuit model;

[0136...

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Abstract

The invention discloses a Kalman filter lithium battery SOC estimation method based on model parameter optimization. The method comprises a step of establishing a second-order RC equivalent circuit model of a lithium battery, a step of identifying parameters of the second-order RC equivalent circuit model on the basis of obtaining an OCV-SOC relationship curve, a step of verifying the accuracy ofthe model, a step of establishing a Kalman filter algorithm based on the second-order RC equivalent circuit model, a step of optimizing the model parameters, and a step of estimating an SOC value of the lithium battery by using the Kalman filter based on the optimized second-order RC equivalent circuit model parameters. The method is simple and reliable, the data is accurate, an estimation error is significantly lower than that before optimization, the online estimation accuracy of SOC is greatly improved, the remaining power of the lithium battery can be accurately reflected, and the method has great significance for improving the safety reliability of the lithium battery, improving the energy utilization rate of the lithium battery and prolonging the service life of the lithium battery.

Description

technical field [0001] The invention relates to the field of electric vehicle lithium battery management systems, in particular to a method for estimating the SOC of a lithium battery with a Kalman filter based on model parameter optimization. Background technique [0002] With the deteriorating global air quality and the gradual scarcity of oil resources, electric vehicles have become the development focus of major automobile companies in the world today. Lithium battery is the energy source of electric vehicles, and its SOC is used to directly reflect the remaining power of the lithium battery, which is an important basis for the vehicle control system to formulate an optimal energy management strategy. It is of great significance to improve the performance, improve the energy utilization rate of lithium batteries, and prolong the life of lithium batteries. [0003] Due to the nonlinear characteristics of lithium batteries, SOC cannot be directly obtained by sensors, and ...

Claims

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Application Information

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IPC IPC(8): G01R31/367G01R31/388G01R31/389G01R31/374G01R31/396
CPCG01R31/367G01R31/374G01R31/388G01R31/389G01R31/396
Inventor 郭向伟司阳王国东许孝卓胡治国耿佳豪
Owner HENAN POLYTECHNIC UNIV
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